A detector array is a combination of individual detectors that are typically arranged in a lattice-like array. The individual detectors of the array are often referred to as the array elements or pixels—a short-hand phrase for picture elements. Each pixel converts the energy from infrared or other electromagnetic (em) radiation into electrical signals. Various techniques for processing these electrical signals often involve quantizing the electrical signals so that they can be represented in digital form.
An example of a detector array is the focal-plane array (FPA), which comprises optics and infrared or visible-light sensor elements for imaging objects or scenes. The FPA is typically constructed as a grid of independent photodetectors that are arrayed in the focal plane of an imaging lens. Functionally, FPA-based imaging is accomplished by optically focusing a desired scene on the lattice-like array so that each sensor element images a portion of the scene. The FPA is used in a wide variety of imaging systems.
An inherent limitation on the quality of the resulting images obtained with detector-array imaging systems is spacial nonuniformity in the photoresponse of the detectors in the array, especially when operating in the infrared (IR) domain. The effect is fixed-pattern noise that is superimposed on the true image and that reduces the resolving capability of the imaging system. Additionally, the nonuniformity slowly and randomly drifts over time, which makes solving the problem permanently with an initial calibration of the system very difficult if not impossible.
Moreover, because of manufacturing constraints and varied environmental conditions, the individual detectors of a detector array frequently fail to have identical operating characteristics. Therefore, substantially similar levels of infrared or other em radiation at two different detectors may generate different responses at each of the detectors.
To the extent that two detectors generate different electrical responses upon exposure to the same level of radiation, it may be said that the detectors are displaying “spatial non-uniformity”. Spatial non-uniformity between detectors may be caused by one or more of the following factors: fixed pattern noise that includes individual detector offsets, residual gain error in the detectors, fixed pattern electronic noise, and/or non-dithered optical structure in the detectors field of view. So-called pixel offset errors in a detector may be modeled by adding a fixed DC value to the ideal response of each detector, and pixel gain errors in a detector may be modeled by scaling the ideal response in each detector.
Different scene-based nonuniformity correction (NUC) algorithms have been proposed. The proposed algorithm-based techniques typically use a digital image sequence and rely on motion to provide diversity in the irradiance observed by each detector. Some scene-based algorithms in the literature repeatedly compensate for gain and bias nonuniformity. These algorithms rely on the concept of constant statistics, which inevitably requires that, over time, the mean and variance of the irradiances of a scene become spatially invariant.
Other proposed techniques use a statistical algorithm based on the assumption that all detectors in an array are exposed to the same range of collected irradiance within a sequence of frames. This particular technique therefore relaxes the constant-statistics assumption, substituting for it a constant-range assumption. Yet another proposed technique involves motion-based algorithms, which posit that detectors should have an identical response when observing the same portion of a scene at different times. Other proposed techniques are intended to exploit shift information between two consecutive frames in order to apply interpolation. These algebraic approaches, however, generally only correct for offsets.
An alternative approach for correcting fixed pattern noise errors relies on a predetermined calibration of the detector array, the calibration being done at the time of fabrication of the array. This so-called factory-based calibration involves exposing the array to a uniform source and tabulating the response of each detector in the array. The tabulated entries include gain and offset corrections for each detector in the array. The entries in the table may be applied against corresponding detectors to generate a corrected image.
Factory-based calibration, however, generally suffers from multiple drawbacks. First, the pixel offset errors may not be linearly dependent; rather they may have non-linear temperature variations. Thus, factory-based calibration must take place over a broad range of temperatures to perform effectively. Second, this proposed solution typically cannot correct for short-term temporal variations in pixel offset error that occur during operation of the array. For instance, variations in temperature of the detector array can create significant offset variations over time. Finally, factory-based calibration normally requires recalibration to correct for long-term unpredictable changes in pixel offset errors that occur as the array components age.
Yet another proposed alternative solution seeks to mitigate the disadvantages associated with factory-based calibration by calibrating the focal plane array while the array is in use. This can be done by placing a rotating plate in front of the detector array so that the array is alternately exposed to the image under observation and to a signal of known intensity. The fixed pattern noise may then be removed by subtracting a detector's response to the known signal from the detector's response to the observed image. This solution typically has two drawbacks, however. First, by requiring a means for alternately exposing the array to the observed image and to a signal of known intensity, additional complex mechanical or optical elements are typically necessary. Second, by requiring that the focal plane array spend time viewing a signal of known intensity instead of the scene under observation, this solution almost inevitably degrades the array's ability to track fast moving objects and reduces the potential signal to noise ratio of the sensor output.
There thus remains a need for a system and methods that effectively and efficiently address the spatial nonuniformity problem inherent in FPAs and other detector arrays. In particular, there is a need for a system and methods that solve the problem without requiring the addition of unwieldy or inordinately expensive components and whose robustness is not constrained by the assumptions inherent in many of the proposed algorithm-based techniques for addressing the problem.